Martin J. Wainwright
Orcid: 0000-0002-8760-2236Affiliations:
- University of California, Berkeley, USA
According to our database1,
Martin J. Wainwright
authored at least 245 papers
between 1999 and 2024.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on zbmath.org
-
on orcid.org
-
on d-nb.info
On csauthors.net:
Bibliography
2024
Taming "data-hungry" reinforcement learning? Stability in continuous state-action spaces.
CoRR, 2024
2023
Doubly High-Dimensional Contextual Bandits: An Interpretable Model for Joint Assortment-Pricing.
CoRR, 2023
Noisy recovery from random linear observations: Sharp minimax rates under elliptical constraints.
CoRR, 2023
Proceedings of the Learning for Dynamics and Control Conference, 2023
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023
2022
J. Mach. Learn. Res., 2022
Policy evaluation from a single path: Multi-step methods, mixing and mis-specification.
CoRR, 2022
Off-policy estimation of linear functionals: Non-asymptotic theory for semi-parametric efficiency.
CoRR, 2022
CoRR, 2022
CoRR, 2022
CoRR, 2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
Proceedings of the International Conference on Machine Learning, 2022
A new similarity measure for covariate shift with applications to nonparametric regression.
Proceedings of the International Conference on Machine Learning, 2022
Optimal and instance-dependent guarantees for Markovian linear stochastic approximation.
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
Proceedings of the Conference on Learning Theory, 2-5 July 2022, London, UK., 2022
2021
IEEE Trans. Inf. Theory, 2021
Instance-Dependent ℓ<sub>∞</sub>-Bounds for Policy Evaluation in Tabular Reinforcement Learning.
IEEE Trans. Inf. Theory, 2021
SIAM J. Math. Data Sci., 2021
J. Mach. Learn. Res., 2021
Instance-optimality in optimal value estimation: Adaptivity via variance-reduced Q-learning.
CoRR, 2021
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021
2020
The Local Geometry of Testing in Ellipses: Tight Control via Localized Kolmogorov Widths.
IEEE Trans. Inf. Theory, 2020
Derivative-Free Methods for Policy Optimization: Guarantees for Linear Quadratic Systems.
J. Mach. Learn. Res., 2020
Fast mixing of Metropolized Hamiltonian Monte Carlo: Benefits of multi-step gradients.
J. Mach. Learn. Res., 2020
CoRR, 2020
Proceedings of the 2020 IEEE Symposium on Security and Privacy, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020
On Linear Stochastic Approximation: Fine-grained Polyak-Ruppert and Non-Asymptotic Concentration.
Proceedings of the Conference on Learning Theory, 2020
Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020
2019
Early Stopping for Kernel Boosting Algorithms: A General Analysis With Localized Complexities.
IEEE Trans. Inf. Theory, 2019
Feeling the Bern: Adaptive Estimators for Bernoulli Probabilities of Pairwise Comparisons.
IEEE Trans. Inf. Theory, 2019
J. Mach. Learn. Res., 2019
Convergence Guarantees for a Class of Non-convex and Non-smooth Optimization Problems.
J. Mach. Learn. Res., 2019
J. Mach. Learn. Res., 2019
Value function estimation in Markov reward processes: Instance-dependent 𝓁<sub>∞</sub>-bounds for policy evaluation.
CoRR, 2019
Stochastic approximation with cone-contractive operators: Sharp 𝓁<sub>∞</sub>-bounds for Q-learning.
CoRR, 2019
Proceedings of the 7th International Conference on Learning Representations, 2019
2018
Linear Regression With Shuffled Data: Statistical and Computational Limits of Permutation Recovery.
IEEE Trans. Inf. Theory, 2018
CoRR, 2018
Breaking the 1/√n Barrier: Faster Rates for Permutation-based Models in Polynomial Time.
CoRR, 2018
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Proceedings of the 35th International Conference on Machine Learning, 2018
Breaking the $1/\sqrtn$ Barrier: Faster Rates for Permutation-based Models in Polynomial Time.
Proceedings of the Conference On Learning Theory, 2018
Proceedings of the International Conference on Artificial Intelligence and Statistics, 2018
2017
Stochastically Transitive Models for Pairwise Comparisons: Statistical and Computational Issues.
IEEE Trans. Inf. Theory, 2017
Newton Sketch: A Near Linear-Time Optimization Algorithm with Linear-Quadratic Convergence.
SIAM J. Optim., 2017
J. Mach. Learn. Res., 2017
J. Mach. Learn. Res., 2017
The local geometry of testing in ellipses: Tight control via localized Kolomogorov widths.
CoRR, 2017
The geometry of hypothesis testing over convex cones: Generalized likelihood tests and minimax radii.
CoRR, 2017
CoRR, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Proceedings of the 2017 IEEE International Symposium on Information Theory, 2017
Proceedings of the 34th International Conference on Machine Learning, 2017
QuTE: Decentralized multiple testing on sensor networks with false discovery rate control.
Proceedings of the 56th IEEE Annual Conference on Decision and Control, 2017
Proceedings of the 55th Annual Allerton Conference on Communication, 2017
Proceedings of the 20th International Conference on Artificial Intelligence and Statistics, 2017
2016
J. Mach. Learn. Res., 2016
Iterative Hessian Sketch: Fast and Accurate Solution Approximation for Constrained Least-Squares.
J. Mach. Learn. Res., 2016
J. Mach. Learn. Res., 2016
CoRR, 2016
CoRR, 2016
Asymptotic behavior of ℓ<sub>p</sub>-based Laplacian regularization in semi-supervised learning.
CoRR, 2016
Local Maxima in the Likelihood of Gaussian Mixture Models: Structural Results and Algorithmic Consequences.
Proceedings of the Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, 2016
Proceedings of the IEEE International Symposium on Information Theory, 2016
Proceedings of the 54th Annual Allerton Conference on Communication, 2016
2015
IEEE Trans. Inf. Theory, 2015
Optimal Rates for Zero-Order Convex Optimization: The Power of Two Function Evaluations.
IEEE Trans. Inf. Theory, 2015
Divide and conquer kernel ridge regression: a distributed algorithm with minimax optimal rates.
J. Mach. Learn. Res., 2015
Regularized M-estimators with nonconvexity: statistical and algorithmic theory for local optima.
J. Mach. Learn. Res., 2015
CoRR, 2015
CoRR, 2015
Newton Sketch: A Linear-time Optimization Algorithm with Linear-Quadratic Convergence.
CoRR, 2015
Fast low-rank estimation by projected gradient descent: General statistical and algorithmic guarantees.
CoRR, 2015
Distributed Estimation of Generalized Matrix Rank: Efficient Algorithms and Lower Bounds.
Proceedings of the 32nd International Conference on Machine Learning, 2015
2014
Early stopping and non-parametric regression: an optimal data-dependent stopping rule.
J. Mach. Learn. Res., 2014
CoRR, 2014
Statistical guarantees for the EM algorithm: From population to sample-based analysis.
CoRR, 2014
Lower bounds on the performance of polynomial-time algorithms for sparse linear regression.
Proceedings of The 27th Conference on Learning Theory, 2014
Stochastic optimization and sparse statistical recovery: An optimal algorithm for high dimensions.
Proceedings of the 48th Annual Conference on Information Sciences and Systems, 2014
2013
Stochastic Belief Propagation: A Low-Complexity Alternative to the Sum-Product Algorithm.
IEEE Trans. Inf. Theory, 2013
J. Mach. Learn. Res., 2013
Belief propagation for continuous state spaces: stochastic message-passing with quantitative guarantees.
J. Mach. Learn. Res., 2013
Distance-based and continuum Fano inequalities with applications to statistical estimation.
CoRR, 2013
CoRR, 2013
Information-theoretic lower bounds for distributed statistical estimation with communication constraints.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013
Proceedings of the 54th Annual IEEE Symposium on Foundations of Computer Science, 2013
2012
Information-Theoretic Limits of Selecting Binary Graphical Models in High Dimensions.
IEEE Trans. Inf. Theory, 2012
Information-Theoretic Lower Bounds on the Oracle Complexity of Stochastic Convex Optimization.
IEEE Trans. Inf. Theory, 2012
Dual Averaging for Distributed Optimization: Convergence Analysis and Network Scaling.
IEEE Trans. Autom. Control., 2012
Minimax-Optimal Rates For Sparse Additive Models Over Kernel Classes Via Convex Programming.
J. Mach. Learn. Res., 2012
Restricted Strong Convexity and Weighted Matrix Completion: Optimal Bounds with Noise.
J. Mach. Learn. Res., 2012
J. Approx. Theory, 2012
CoRR, 2012
Proceedings of the IEEE Statistical Signal Processing Workshop, 2012
Structure estimation for discrete graphical models: Generalized covariance matrices and their inverses.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
Stochastic optimization and sparse statistical recovery: Optimal algorithms for high dimensions.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012
Quantized stochastic belief propagation: Efficient message-passing for continuous state spaces.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012
Corrupted and missing predictors: Minimax bounds for high-dimensional linear regression.
Proceedings of the 2012 IEEE International Symposium on Information Theory, 2012
Proceedings of the 51th IEEE Conference on Decision and Control, 2012
Proceedings of the 50th Annual Allerton Conference on Communication, 2012
2011
IEEE Trans. Signal Process., 2011
Minimax Rates of Estimation for High-Dimensional Linear Regression Over <sub>q</sub> -Balls.
IEEE Trans. Inf. Theory, 2011
Simultaneous Support Recovery in High Dimensions: Benefits and Perils of Block <sub>1</sub>/ <sub>INFINITY </sub> -Regularization.
IEEE Trans. Inf. Theory, 2011
Non-Asymptotic Analysis of an Optimal Algorithm for Network-Constrained Averaging With Noisy Links.
IEEE J. Sel. Top. Signal Process., 2011
Fast global convergence of gradient methods for high-dimensional statistical recovery
CoRR, 2011
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011
High-dimensional regression with noisy and missing data: Provable guarantees with non-convexity.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 12-14 December 2011, 2011
Proceedings of the 28th International Conference on Machine Learning, 2011
Early stopping for non-parametric regression: An optimal data-dependent stopping rule.
Proceedings of the 49th Annual Allerton Conference on Communication, 2011
Proceedings of the 49th Annual Allerton Conference on Communication, 2011
2010
Information-theoretic limits on sparse signal recovery: dense versus sparse measurement matrices.
IEEE Trans. Inf. Theory, 2010
Lossy source compression using low-density generator matrix codes: analysis and algorithms.
IEEE Trans. Inf. Theory, 2010
Estimating Divergence Functionals and the Likelihood Ratio by Convex Risk Minimization.
IEEE Trans. Inf. Theory, 2010
IEEE Trans. Inf. Theory, 2010
IEEE J. Solid State Circuits, 2010
Message-passing for Graph-structured Linear Programs: Proximal Methods and Rounding Schemes.
J. Mach. Learn. Res., 2010
J. Mach. Learn. Res., 2010
High-dimensional Variable Selection with Sparse Random Projections: Measurement Sparsity and Statistical Efficiency.
J. Mach. Learn. Res., 2010
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
Fast global convergence rates of gradient methods for high-dimensional statistical recovery.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010
Proceedings of the IEEE International Symposium on Information Theory, 2010
Proceedings of the IEEE International Symposium on Information Theory, 2010
Proceedings of the 27th International Conference on Machine Learning (ICML-10), 2010
Lossy source coding with sparse graph codes: A variational formulation of soft decimation.
Proceedings of the 48th Annual Allerton Conference on Communication, 2010
2009
Low-Density Graph Codes That Are Optimal for Binning and Coding With Side Information.
IEEE Trans. Inf. Theory, 2009
Information-theoretic limits on sparsity recovery in the high-dimensional and noisy setting.
IEEE Trans. Inf. Theory, 2009
Sharp thresholds for high-dimensional and noisy sparsity recovery using l1-constrained quadratic programming (Lasso).
IEEE Trans. Inf. Theory, 2009
IEEE Trans. Inf. Theory, 2009
Design of LDPC decoders for improved low error rate performance: quantization and algorithm choices.
IEEE Trans. Commun., 2009
Predicting error floors of structured LDPC codes: deterministic bounds and estimates.
IEEE J. Sel. Areas Commun., 2009
Simultaneous support recovery in high dimensions: Benefits and perils of block l<sub>1</sub>/l<sub>infinity</sub>-regularization
CoRR, 2009
Minimax rates of estimation for high-dimensional linear regression over $\ell_q$-balls.
CoRR, 2009
Lower bounds on minimax rates for nonparametric regression with additive sparsity and smoothness.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
A unified framework for high-dimensional analysis of $M$-estimators with decomposable regularizers.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 7-10 December 2009, 2009
Proceedings of the 47th Annual Allerton Conference on Communication, 2009
2008
IEEE Trans. Signal Process., 2008
IEEE Trans. Signal Process., 2008
On Optimal Quantization Rules for Some Problems in Sequential Decentralized Detection.
IEEE Trans. Inf. Theory, 2008
Found. Trends Mach. Learn., 2008
High-dimensional subset recovery in noise: Sparsified measurements without loss of statistical efficiency
CoRR, 2008
Model Selection in Gaussian Graphical Models: High-Dimensional Consistency of l<sub>1</sub>-regularized MLE.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Proceedings of the Advances in Neural Information Processing Systems 21, 2008
Information-theoretic limits on sparse support recovery: Dense versus sparse measurements.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008
High-dimensional subset recovery in noise: Sparse measurements and statistical efficiency.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008
High-dimensional analysis of semidefinite relaxations for sparse principal components.
Proceedings of the 2008 IEEE International Symposium on Information Theory, 2008
Message-passing for graph-structured linear programs: proximal projections, convergence and rounding schemes.
Proceedings of the Machine Learning, 2008
Proceedings of the Global Communications Conference, 2008. GLOBECOM 2008, New Orleans, LA, USA, 30 November, 2008
Spectral clustering in high-dimensions: Necessary and sufficient conditions for dense and sparse mixtures.
Proceedings of the 46th Annual Allerton Conference on Communication, 2008
Proceedings of the 46th Annual Allerton Conference on Communication, 2008
Proceedings of the 46th Annual Allerton Conference on Communication, 2008
2007
CoRR, 2007
CoRR, 2007
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Estimating divergence functionals and the likelihood ratio by penalized convex risk minimization.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Information-theoretic bounds on sparsity recovery in the high-dimensional and noisy setting.
Proceedings of the IEEE International Symposium on Information Theory, 2007
Proceedings of the IEEE International Symposium on Information Theory, 2007
Proceedings of the 6th International Conference on Information Processing in Sensor Networks, 2007
Proceedings of the INFOCOM 2007. 26th IEEE International Conference on Computer Communications, 2007
Proceedings of IEEE International Conference on Communications, 2007
Proceedings of IEEE International Conference on Communications, 2007
2006
Log-determinant relaxation for approximate inference in discrete Markov random fields.
IEEE Trans. Signal Process., 2006
Data association based on optimization in graphical models with application to sensor networks.
Math. Comput. Model., 2006
J. Mach. Learn. Res., 2006
Inconsistent parameter estimation in Markov random fields: Benefits in the computation-limited setting
CoRR, 2006
High-Dimensional Graphical Model Selection Using ℓ<sub>1</sub>-Regularized Logistic Regression.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006
Low-density constructions for lossy compression, binning, and coding with side information.
Proceedings of the 2006 IEEE Information Theory Workshop, 2006
Universal Quantile Estimation with Feedback in the Communication-Constrained Setting.
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006
Proceedings of the Proceedings 2006 IEEE International Symposium on Information Theory, 2006
Proceedings of the Fifth International Conference on Information Processing in Sensor Networks, 2006
Investigation of Error Floors of Structured Low-Density Parity-Check Codes by Hardware Emulation.
Proceedings of the Global Telecommunications Conference, 2006. GLOBECOM '06, San Francisco, CA, USA, 27 November, 2006
Proceedings of the 2006 Data Compression Conference (DCC 2006), 2006
2005
IEEE Trans. Signal Process., 2005
IEEE Trans. Inf. Theory, 2005
IEEE Trans. Inf. Theory, 2005
IEEE Trans. Inf. Theory, 2005
CoRR, 2005
Proceedings of the UAI '05, 2005
Estimating the wrong Markov random field: Benefits in the computation-limited setting.
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Proceedings of the Advances in Neural Information Processing Systems 18 [Neural Information Processing Systems, 2005
Lossy source encoding via message-passing and decimation over generalized codewords of LDGM codes.
Proceedings of the 2005 IEEE International Symposium on Information Theory, 2005
2004
IEEE Trans. Signal Process., 2004
Tree consistency and bounds on the performance of the max-product algorithm and its generalizations.
Stat. Comput., 2004
Proceedings of the Machine Learning, 2004
2003
Tree-based reparameterization framework for analysis of sum-product and related algorithms.
IEEE Trans. Inf. Theory, 2003
IEEE Trans. Image Process., 2003
Proceedings of the Advances in Neural Information Processing Systems 16 [Neural Information Processing Systems, 2003
Tree-reweighted belief propagation algorithms and approximate ML estimation by pseudo-moment matching.
Proceedings of the Ninth International Workshop on Artificial Intelligence and Statistics, 2003
2002
PhD thesis, 2002
Statistical and Information-Theoretic Methods for Self-Organization and Fusion of Multimodal, Networked Sensors.
Int. J. High Perform. Comput. Appl., 2002
Proceedings of the Advances in Neural Information Processing Systems 15 [Neural Information Processing Systems, 2002
2001
Proceedings of the Advances in Neural Information Processing Systems 14 [Neural Information Processing Systems: Natural and Synthetic, 2001
Adaptive Wiener denoising using a Gaussian scale mixture model in the wavelet domain.
Proceedings of the 2001 International Conference on Image Processing, 2001
2000
Proceedings of the Advances in Neural Information Processing Systems 13, 2000
Random Cascades of Gaussian Scale Mixtures and Their Use in Modeling Natural Images With Application to Denoising.
Proceedings of the 2000 International Conference on Image Processing, 2000
1999
Proceedings of the Advances in Neural Information Processing Systems 12, [NIPS Conference, Denver, Colorado, USA, November 29, 1999